
import geopandas as gpd
import altair as alt
import  pandas as pd


trends = pd.read_csv("population_trends.csv")


trends.head()


ukraine = gpd.read_file('ukraine.json')
ukraine.head()


trends = trends[trends['region'] != 'Ukraine'] # clean up data
latest = trends[trends['year'] == trends['year'].max()]
latest


ukraine = ukraine[['NAME_1', 'geometry']]
ukraine.columns = ['region', 'geometry'] # need to rename columns for transform_lookup


rate_map = alt.Chart(ukraine, title='Population rate of 2019 by region').transform_lookup(
    lookup = 'region',
    from_ = alt.LookupData(data = latest, 
                           key = 'region',
                           fields=['rate'])
).mark_geoshape(color ='lightgray', stroke = 'white', strokeWidth = 1
).encode(
    color = alt.Color('rate:Q', scale=alt.Scale(scheme='reds', reverse = True)),
    tooltip = [
        alt.Tooltip('region:N'),
        alt.Tooltip('rate:Q')
    ]
) + alt.Chart(ukraine[ukraine['region'].isin(latest[latest['rate'].isna()]['region'].tolist())]).mark_geoshape(fill = 'lightgray', stroke = 'white', strokeWidth = 1)

rate_map = rate_map.properties(width = 600, height = 400)


rate_map


trends = trends[(trends['year'] >1988) & (trends['year'] < 2020)]


linear = alt.Chart(trends, title='Population increase\decrease rate by regions over years').mark_line().encode(
    x = alt.X('year:Q', title='Year'),
    y = alt.Y('rate:Q', title="Population change rate"),
    color = alt.Color('region:N', title='Region'),
    tooltip = [alt.Tooltip('region:N', title='Region:')] 
).properties(width = 600, height = 400)

linear


alt.hconcat(rate_map, linear)

	region	year	rate
0	Ukraine	1989	1.7
1	Ukraine	1990	0.5
2	Ukraine	1991	-0.8
3	Ukraine	1992	-2.0
4	Ukraine	1993	-3.5

	GID_0	NAME_0	GID_1	NAME_1	VARNAME_1	NL_NAME_1	TYPE_1	ENGTYPE_1	CC_1	HASC_1	geometry
0	UKR	Ukraine	UKR.1_1	Cherkasy	Cherkas'ka Oblast'\|Cherkasskaya Oblast'\|Cherkassy	None	Oblast'	Region	None	UA.CK	MULTIPOLYGON (((31.32614 48.74507, 31.31716 48...
1	UKR	Ukraine	UKR.2_1	Chernihiv	Chernigov\|Tschernigow	None	Oblast'	Region	None	UA.CH	MULTIPOLYGON (((33.09283 50.50966, 33.09261 50...
2	UKR	Ukraine	UKR.3_1	Chernivtsi	Chernivets'ka Oblast'\|Chernovitskaya Oblast'\|C...	None	Oblast'	Region	None	UA.CV	MULTIPOLYGON (((24.93280 47.72794, 24.93301 47...
3	UKR	Ukraine	UKR.4_1	Crimea	Crimée\|Criméia\|Krim\|Krymskaya Respublika\|Respu...	None	Autonomous Republic	Autonomous Republic	None	UA.KR	MULTIPOLYGON (((33.79291 44.39153, 33.79465 44...
4	UKR	Ukraine	UKR.5_1	Dnipropetrovs'k	Dnipropetrovsk\|Dniepropietrovsk\|Dnjepropetrowsk	None	Oblast'	Region	None	UA.DP	MULTIPOLYGON (((33.93176 47.48407, 33.92332 47...

	region	year	rate
61	Crimea	2019	NaN
92	Vinnytsya	2019	-7.9
123	Volyn	2019	-2.8
154	Dnipropetrovs'k	2019	-8.9
185	Donets'k	2019	NaN
216	Zhytomyr	2019	-8.5
247	Transcarpathia	2019	-2.0
278	Zaporizhzhya	2019	-9.6
309	Ivano-Frankivs'k	2019	-4.0
340	Kyiv	2019	-8.1
371	Kirovohrad	2019	-9.6
402	Luhans'k	2019	NaN
433	L'viv	2019	-4.3
464	Mykolayiv	2019	-8.1
495	Odesa	2019	-5.1
526	Poltava	2019	-9.9
557	Rivne	2019	-1.6
588	Sumy	2019	-10.2
619	Ternopil'	2019	-6.6
650	Kharkiv	2019	-8.4
681	Kherson	2019	-7.4
712	Khmel'nyts'kyy	2019	-7.5
743	Cherkasy	2019	-10.0
774	Chernivtsi	2019	-3.1
805	Chernihiv	2019	-12.5
836	Kyiv City	2019	-0.2
867	Sevastopol'	2019	NaN

Використовуючи запропоновані дані, створіть складне представлення даних з наступними елементами¶

1. Map of increase\decrease population rate per each region over the last available year¶

Build the colored map composed out of Ukrainian regions with rate data and Crimea, Donets'k and Luhans'k as gray - for no data available as provided in the example¶

2. Liniar representation of rate change over the years: one line per each region¶

Build the trend for each region¶

Join two charts¶